English

On Sidorenko's conjecture for determinants and Gaussian Markov random fields

Probability 2017-01-16 v1 Combinatorics

Abstract

We study a class of determinant inequalities that are closely related to Sidorenko's famous conjecture (Also conjectured by Erd\H os and Simonovits in a different form). Our results can also be interpreted as entropy inequalities for Gaussian Markov random fields (GMRF). We call a GMRF on a finite graph GG homogeneous if the marginal distributions on the edges are all identical. We show that if GG satisfies Sidorenko's conjecture then the differential entropy of any homogeneous GMRF on GG is at least E(G)|E(G)| times the edge entropy plus V(G)2E(G)|V(G)|-2|E(G)| times the point entropy. We also prove this inequality in a large class of graphs for which Sidorenko's conjecture is not verified including the so-called M\"obius ladder: K5,5C10K_{5,5}\setminus C_{10}. The connection between Sidorenko's conjecture and GMRF's is established via a large deviation principle on high dimensional spheres combined with graph limit theory.

Keywords

Cite

@article{arxiv.1701.03632,
  title  = {On Sidorenko's conjecture for determinants and Gaussian Markov random fields},
  author = {Balazs Szegedy},
  journal= {arXiv preprint arXiv:1701.03632},
  year   = {2017}
}
R2 v1 2026-06-22T17:49:29.033Z